Characterization and Comparison of GITR Expression in Solid Tumors

Abstract

Purpose: Determine the differential effect of a FcγR-binding, mIgG2a anti-GITR antibody in mouse tumor models, and characterize the tumor microenvironment for the frequency of GITR expression in T-cell subsets from seven different human solid tumors.Experimental Design: For mouse experiments, wild-type C57BL/6 mice were subcutaneously injected with MC38 cells or B16 cells, and BALB/c mice were injected with CT26 cells. Mice were treated with the anti-mouse GITR agonist antibody 21B6, and tumor burden and survival were monitored. GITR expression was evaluated at the single-cell level using flow cytometry (FC). A total of 213 samples were evaluated for GITR expression by IHC, 63 by FC, and 170 by both in seven human solid tumors: advanced hepatocellular carcinoma, non-small cell lung cancer (NSCLC), renal cell carcinoma, pancreatic carcinoma, head and neck carcinoma, melanoma, and ovarian carcinoma.

Results: The therapeutic benefit of 21B6 was greatest in CT26 followed by MC38, and was least in the B16 tumor model. The frequency of CD8 T cells and effector CD4 T cells within the immune infiltrate correlated with response to treatment with GITR antibody. Analysis of clinical tumor samples showed that NSCLC, renal cell carcinoma, and melanoma had the highest proportions of GITR-expressing cells and highest per-cell density of GITR expression on CD4⁺ Foxp3⁺ T regulatory cells. IHC and FC data showed similar trends with a good correlation between both techniques.

Conclusions: Human tumor data suggest that NSCLC, renal cell carcinoma, and melanoma should be the tumor subtypes prioritized for anti-GITR therapy development.

Figure 1.. Effect of anti-GITR antibody treatment on three different mouse tumor models.

Three different mouse tumor models, CT26 colon carcinoma (a-d), MC38 colon carcinoma (e-g), and B16 melanoma (h-k), were developed by subcutaneous inoculation of tumor cells. Mice were treated with three doses of anti-GITR antibody 21B6 delivered intraperitoneally. CT26 tumor growth in 21B6-treated mice was inhibited by 94.17% (b) compared to the tumor growth in isotype-treated mice (a). Tumor growth inhibition (c) and survival (d) were significantly greater in 21B6-treated mice than in isotype-control-treated mice. 21B6 was less effective against MC38 tumors: tumor growth in 21B6-treated mice was inhibited by 57.85% (f) compared to the tumor growth in control mice (e), and this inhibition was significant (g). Survival could not be calculated in the MC38 model because of tumor ulceration. 21B6 had the least therapeutic benefit for B16 tumors, in which 21B6 resulted in 27.85% tumor growth inhibition (i, j) compared to the tumor growth in control mice (h), and no survival improvement (k). Data are representative of 2–4 experiments per tumor model. CR, complete response; TGI, tumor growth inhibition. **, p ≤ 0.01.

Figure 2.. The frequency of effector T cells (CD8 and CD4) in three different mouse tumor models correlates with response to anti-GITR antibody.

TILs were profiled by FC 2 days after the third and final antibody treatment. Shown are the percentages of TILs expressing GITR (a); the frequencies of TILs that were CD4 Tregs (b), CD4 Teff cells (c), and CD8 T cells (d); and the frequencies of GITR⁺ cells within the CD4 Treg (e), CD4 Teff cell (f), and CD8 T cell (g) TIL fractions. *, p ≤ 0.05; **, p ≤ 0.01; ***, p ≤ 0.001 by 1-way ANOVA followed by Tukey’s multiple comparison test.

Figure 3.. GITR expression within the tumor microenvironment is associated with a high frequency of TILs.

(a-c) IHC analyses of (a) GITR expression, (b) CD8 expression, and (c) CD4 expression in HCC, NSCLC, RCC, pancreatic carcinoma (PaCa), and head and neck carcinoma (H&N). (c) Representative single stain IHC images showing CD4; CD8; GITR expression in NSCLC, RCC and PaCa. (e) Regression analysis showing comparison of findings of IHC and FC from the three tumor types analyzed by both methods using regression showing expression of CD4, CD3, CD8, Treg/Foxp3, and GITR. The two methods showed strong positive correlation for HCC, NSCLC, and RCC. *, p ≤ 0.05; **, p ≤ 0.01; ***, p ≤ 0.001; ****, p ≤ 0.0001. Numbers of tumor samples analyzed are shown in Table 1.

Figure 4.. The frequency of expression of GITR is higher in Tregs than in effector T cells (CD4 and CD8).

Using FC, the frequencies of GITR⁺ cells as a fraction of CD4 Tregs, CD4 Teff cells, and CD8 T cells were calculated for HCC (a), NSCLC (b), RCC (c) and Melanoma (d). *, p ≤ 0.05; **, p ≤ 0.01; ***, p ≤ 0.001; ****, p ≤ 0.0001. Numbers of tumor samples analyzed are shown in Table 1.

Figure 5.. The amount of GITR on a per-cell basis is higher in Tregs than in effector T cells (CD4 and CD8).

Using FC, the MFI of CD4⁺GITR⁺ Tregs, CD4⁺GITR⁺ Teff cells, and CD8⁺GITR⁺ T cells was measured in HCC (a), NSCLC (b) RCC (c) and Mel (d). * indicates, p ≤ 0.05; **, p ≤ 0.01; ***, p ≤ 0.001; ****, p ≤ 0.0001. Numbers of tumor samples analyzed are shown in Table 1.